AC cross-border-ecommerce-compliance
跨境电商产品合规速查（8品类×8市场）。用户输入产品类别和目的地国家/市场， 自动查询并输出该品类在该市场的全套合规要求：产品认证、标签规范、包装要求、 测试标准、限制物质/禁用成分、进口文件清单、平台额外要求（如亚马逊合规）、 特殊注意事项。覆盖电子产品/玩具/化妆品/食品/纺织品/医疗器械/家居用品/ 儿童用品 8 大品类 × 美国/欧盟/英国/日本/澳大利亚/加拿大/韩国/中东GCC 8 大市场。输出交互式 HTML 可视化合规报告。 触发场景：出口合规、认证查询、亚马逊合规、产品出口手续、 "出口需要什么认证"、"出口到 XX 要什么手续"、"XX 产品出口 XX 合规"、 "跨境电商合规"、"目的国认证"、"FCC CE UKCA PSE KC RCM 认证"等。
跨境电商产品合规速查（8品类×8市场）。用户输入产品类别和目的地国家/市场， 自动查询并输出该品类在该市场的全套合规要求：产品认证、标签规范、包装要求、 测试标准、限制物质/禁用成分、进口文件清单、平台额外要求（如亚马逊合规）、 特殊注意事项。覆盖电子产品/玩具/化妆品/食品/纺织品/医疗器械/家居用品/ 儿童用品…
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "agent_created"
Process rating: all ten parameters 53/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 100Tools and files. No external tools needed
- 100Steps. 60 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 865 tokens
- 100Running it twice. No mutating operations
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +5Description quotes 5 example trigger phrases
- +3Description length 341: enough signal without eating the budget
- +4Structure: 15 headings
- +3Step-by-step instructions: 60 items
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.